Update app.py

app.py

@@ -26,24 +26,22 @@ with gr.Blocks() as demo:
             with gr.Row():
                 output_message = gr.Textbox(label="Output Message",interactive=False)
                 output_audio = gr.Audio(label="Output Audio",interactive=False)
-            #run_btn.click(run_inference, [model_name, pitch, input_path, f0_method, save_as, index_rate, volume_normalization, consonant_protection], output_message)
-        with gr.Tab("# Training"):
-             model_name = gr.Textbox(label="Model Name (No spaces or symbols)")
-             dataset_folder = gr.Textbox(label="Dataset Folder", value="/content/dataset")
-             f0method = gr.Dropdown(["pm", "harvest", "rmvpe", "rmvpe_gpu"], label="F0 Method", value="rmvpe_gpu")
-             
-             preprocess_btn = gr.Button("Start Preprocessing")
-             f0_btn = gr.Button("Extract F0 Feature")
-             train_btn = gr.Button("Train Index")
+            run_btn.click(run_inference, [model_name, pitch, input_path, f0_method, save_as, index_rate, volume_normalization, consonant_protection], output_message)
 
+        with gr.Tab("Training"):\
+            model_name = gr.Textbox(label="Model Name (No spaces or symbols)")
+            dataset_folder = gr.Textbox(label="Dataset Folder", value="/content/dataset")
+            f0method = gr.Dropdown(["pm", "harvest", "rmvpe", "rmvpe_gpu"], label="F0 Method", value="rmvpe_gpu")
+             
+            preprocess_btn = gr.Button("Start Preprocessing")
+            f0_btn = gr.Button("Extract F0 Feature")
+            train_btn = gr.Button("Train Index")
             preprocess_output = gr.Textbox(label="Preprocessing Log")
             f0_output = gr.Textbox(label="F0 Feature Extraction Log")
             train_output = gr.Textbox(label="Training Log")
 
-            #preprocess_btn.click(preprocess_data, inputs=[model_name, dataset_folder], outputs=preprocess_output)
-            #f0_btn.click(extract_f0_feature, inputs=[model_name, f0method], outputs=f0_output)
-            #train_btn.click(train_index, inputs=[model_name, "v2"], outputs=train_output)
-
-    
+            preprocess_btn.click(preprocess_data, inputs=[model_name, dataset_folder], outputs=preprocess_output)
+            f0_btn.click(extract_f0_feature, inputs=[model_name, f0method], outputs=f0_output)
+            train_btn.click(train_index, inputs=[model_name, "v2"], outputs=train_output)
     
-demo.launch()
+demo.launch()